Scientific benchmarks for guiding macromolecular energy function improvement
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Updated: May 14, 2026

Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules
Published on: July 25, 2013
Andrew Leaver-Fay1, Matthew J O'Meara, Mike Tyka
1Department of Biochemistry, University of North Carolina, Chapel Hill, North Carolina, USA. leaverfa@email.unc.edu
Abstract:
Accurate energy functions are critical to macromolecular modeling and design. We describe new tools for identifying inaccuracies in energy functions and guiding their improvement, and illustrate the application of these tools to the improvement of the Rosetta energy function. The feature analysis tool identifies discrepancies between structures deposited in the PDB and low-energy structures generated by Rosetta; these likely arise from inaccuracies in the energy function. The optE tool optimizes the weights on the different components of the energy function by maximizing the recapitulation of a wide range of experimental observations. We use the tools to examine three proposed modifications to the Rosetta energy function: improving the unfolded state energy model (reference energies), using bicubic spline interpolation to generate knowledge-based torisonal potentials, and incorporating the recently developed Dunbrack 2010 rotamer library (Shapovalov & Dunbrack, 2011).
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Most macromolecules are composed of single subunits, or building blocks, called monomers. The monomers combine with each other using covalent bonds to form larger molecules known as polymers.
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